docstr: Set summary information during the training process for visualization purposes.
  Saved summary can be viewed via TensorBoard.
  In order to take effect, it needs to be called before fit.
  
  Training summary will be saved to 'log_dir/app_name/train'
  and validation summary (if any) will be saved to 'log_dir/app_name/validation'.
  
  :param log_dir: The base directory path to store training and validation logs.
  :param app_name: The name of the application.
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code: def set_tensorboard(self, log_dir, app_name):
      """
      Set summary information during the training process for visualization purposes.
      Saved summary can be viewed via TensorBoard.
      In order to take effect, it needs to be called before fit.
  
      Training summary will be saved to 'log_dir/app_name/train'
      and validation summary (if any) will be saved to 'log_dir/app_name/validation'.
  
      :param log_dir: The base directory path to store training and validation logs.
      :param app_name: The name of the application.
      """
      self.log_dir = log_dir
      self.app_name = app_name
  
file_path: analytics-zoo/pyzoo/zoo/orca/learn/spark_estimator.py
imports: from abc import abstractmethod
  from zoo.orca.learn.base_estimator import BaseEstimator
label_desc: Use image node_id 7 for calling the Estimator obj's underlying member method code with example usage: obj.set_tensorboard(log_dir, app_name) without return types